bespokedevelopr

https://spacenews.com/chinas-orbital-maneuvers-blur-the-line...

But they also want to taste the sweet fruit of AI so the only way to do this that a CISO will approve is on local air gapped hardware. It’s a niche but still a billion dollar niche.

Basically it’s complicated. Some areas did experience extreme droughts that year and others faired well.

BPA was able to lever up their reserves early due to those same forecasts which allowed them excess supply to sell when other utilities experienced extreme heat (drought) and couldn’t produce enough.

> Notably, Bonneville was able to offer much needed support to other Pacific Northwest and California utilities during late-summer heatwaves and scarcity events. Our hydropower operations planners and traders positioned the power system to maximize supply, enabling us to deliver significant amounts of power across the West to help keep the lights on during a string of energy emergencies.

https://www.bpa.gov/-/media/Aep/finance/annual-reports/ar202...

It started with informal among friends things, and we’ve found through our networks there’s a lot of demand beyond her girlfriends wanting high tea etiquette. Now she's diving into tech people who have elevated into higher ranks but don’t have experience yet in fine dining with clients and leaders.

It’s been a lot of fun doing something that has nothing to do with AI and really minimal tech in general. The events have been a lot of fun, really feels like we’re cooking something.

They are the TJ Maxx of software development.

I personally haven’t expected anything more of them for years. Once you’ve seen how the sausage is made and all that.

I cannot take your comment very serious when so much of it is plainly wrong. You fall into the later category of what I described in my original comment. Outside of reddit-sphere people do not take these flippant and short-sighted comments seriously.

You only have to look at Hermiston/Umatilla OR to see how impactful data centers can be on rural communities. There’s a lot more than 40 new jobs there since Amazon started building data centers.

The other locations like Oracle’s dc in Port Washington or MS in Racine/Kenosha area are located such that they are within the defined boundaries outlined and dc unlike Foxconn are all ‘closed-loop’ which of course isn’t entirely perfect but certainly not on the scale of Foxcon’s 7mil gal/day nonsense.

I also don’t understand the vehement push back against data centers in WI. It is a prime location for both residents and business. WI and all of the upper midwest was gutted of their manufacturing in my parents time. Now companies are bringing back long term commitments and the people there don’t want it?

I can understand not wanting a data center in AZ or NM. But WI has the resources, climate, and power generating capabilities to support this. There is talk of bringing back the Kewaunee nuclear plant even to support growth.

How does a former manufacturing power house state, not want to bring back jobs and the tax revenue a dc will pull in?

One of the boomer-issues I’ve heard, as I characterize it since it comes from my fam, is that data centers along with solar are taking away farm land and they’re pouty about it. However that farm land is soybeans grown for export to other countries, acting as a fresh water subsidy for those places. The farmers aren’t feeding the state anyways.

Most of the fervent opposition however comes from my generation who are mad about AI so therefore data centers can’t be built because they don’t like it. It isn’t a very compelling argument.

Also from what I’ve seen is big city hospitals use a mix of all three. Which I believe actually creates an opening as it shows a willingness to use different walled gardens.

However I think there are a lot of opportunities to just build on top of these systems rather than wholesale replace. Because they’re one size fits all and the people who work on them haven’t a single designer bone in their body the interfaces are terribly clunky and slow. Macros exist but seemingly no one is aware of them. It’s rife to build better interfaces tied into macros behind the scenes.

Started playing with gas town which is really cool. I had a naive version built that was just not good enough. This feels like a step in the right direction.

Haven’t had much time to work on any of my physical hands on hobbies lately but maybe when the weather gets better I’ll head back out to the shop again.

My takeaway is they get it correct enough but no deep insight on the power generation industry.

I was surprised by and learned a few things from the article though. Definitely gives me some ideas of reaching out to old contacts to see if there’s any opportunities with building models and analytics for the new demands.

Focusing on Bloom is fun because they’re new and startup vibes but Innio and cat are really having a resurgence of demand with their generators and building diesel/natg engines is much simpler than gas turbines. I’m sure the heads at GE wish they hadn’t sold that off now.

On steam/gas turbine blade manufacturing there most certainly are more big players than 4 and many US based. You have to remember this is an old industry with existing supply chains and maintenance companies.

As long as the demand for new data centers doesn’t lose steam these onsite options will continue to flourish. Fed grid access builds are currently a 10+ year wait and they are reworking the system to be “fast”, only 5-6 years for build outs now. They’re also changing how the bidding process works which was touched on here. You need skin in the game if you want to be taken seriously now. There’s so many requests from companies arbing who can give them the best deal/timeline. Now you need to put money up if you even want a call back.

I switched over to consulting/contracting so I don’t have the visibility like they do, but my work is heavily dependent on llms. However I don’t see it wiping out the industry but rather making people more efficient.

They have much more robust tooling though around their llms and internal products that have automated much of their workflows which is I believe where the concern is coming from. They can see first hand how much of their job has turned into reviewing outputs and feeding outputs into other tools. A shift in skills but not fully automated solution yet.

It’s hard to gauge where things are going and where we’ll be in 5 years. If we only get incremental improvements there’s still huge gains to be made in building out tooling ecosystems to make this all better.

What does that look like for new college grads though? How much of this is really computer science if you are only an llm consumer?

This was a fascinating read. It’s been a few years since I finished but gives about the most thorough analysis you’ll find.

Not an essay but you can probably find an ai to summarize it for you.

Using it for non-people involved images and it’s pretty good although I haven’t done much and it isn’t doing anything 2.5-flash wasn’t already doing in the same amount of requests.

The feature seems to be poorly implemented by all manufacturers. I see Teslas driving around flashing high beams every night because they trigger on/off really quickly and the drivers seem oblivious to the rapid change.

https://old.reddit.com/r/wallstreetbets/comments/1oz6gjp/new...

It’s incredible to think about what else has happened during these past 10 years of development. Or think about other decade long stretches and what was accomplished.

Not cutting short what the undertaking of this is, just that the scale of this project spanning a decade is fascinating.

Every image/video/text post on a meta app is essentially subsidized by oai/gemini/anthropic as they are all losing money on inference. Meta is getting more engagement and ad sales through these subsidized genai image content posts.

Long term they need to catch up and training/inference costs need to drop enough such that each genai post costs less than net profit on the ads but they’re in a great position to bridge the gap.

The end of all of this is ad sales. Google and Meta are still the leaders of this. OpenAI needs a social engagement platform or it is only going to take a slice of Google.

Instead it will be just as it is has been for years, let’s send this (in this case) AI generated data to Malaysia or Bangladesh and have them clean it up and then bill it as perfect AI solution.

These people in poorer nations have been cleaning data for ML and AI for years. It’s just adding another loop back in.